Publication:
Kernel antenna array processing

Loading...
Thumbnail Image
Identifiers
Publication date
2007-03
Defense date
Advisors
Tutors
Journal Title
Journal ISSN
Volume Title
Publisher
IEEE
Impact
Google Scholar
Export
Research Projects
Organizational Units
Journal Issue
Abstract
We introduce two support vector machine (SVM)-based approaches for solving antenna problems such as beamforming, sidelobe suppression, and maximization of the signal-to-noise ratio. A basic introduction to SVM optimization is provided and a complex nonlinear SVM formulation developed to handle antenna array processing in space and time. The new optimization formulation is compared with both the minimum mean square error and the minimum variance distortionless response methods. Several examples are included to show the performance of the new approaches
Description
Keywords
Kernel method, Beamforming, Array processing, Antenna array, Mercer’s kernels, Support vector machines
Bibliographic citation
IEEE Transactions on Antennas and Propagation, Special Issue on Synthesis and Optimization Techniques in Electromagnetics and Antenna System Design, Vol. 55, Nº 3, pp. 642-650, March 2007